Questions,
answered.

Avisha NessAiver is a biomedical engineer (M.S. in Engineering, University of Maryland, Summa Cum Laude) and science communicator. He is the founder and CEO of Distilled Science LLC, CTO of Birya Biotech, and a Venture Partner at the MedStartr Venture Fund, and has collaborated with the WHO (Operation FIDES) and the UN (Team Halo).

Distilled Science is an evidence-first science communication platform with more than a million followers across TikTok, Instagram, and YouTube. It runs viral health and technology claims through the actual research and reports the verdict, the proof, and what the headline left out.

Nutrition, neuroscience and sleep, health technology, supplements, and health misinformation — the science behind the claims people actually encounter in their feeds.

Two things rarely combine here: the engineering background to read a study properly, and the creator craft to make it watchable. Every claim is cited, mechanism is separated from outcome, and conflicts of interest are flagged. See How I evaluate evidence for the full standard.

Health, wellness, supplement, wearable, and medical-device claims — landing pages, ad scripts, packaging copy, or a specific study a brand wants to cite.

Yes. Supplement studies and wearable/health-tech claims are a core focus, including common failure modes like surrogate endpoints, undisclosed doses, and relative-risk inflation.

Yes — the goal is claims you can stand behind that still convert, not legal-flavored hedging no one reads.

Peer-reviewed human evidence is prioritized, with mechanistic and preclinical work clearly labeled as such. Every scientific claim is cited so you can check the source yourself.

Yes — hooks, scripts, and myth-bust formats that stay accurate while being built for retention on TikTok, Instagram, and YouTube.

Both. I produce creator-led content directly, and I advise in-house teams on evidence-based brand voice and content systems.

That is the point. The same evidence standard that runs the channel keeps brand content from drifting into overstatement or science-washing.

Structuring your site and content so AI systems can retrieve, understand, cite, and recommend it accurately — fact-dense pages, clear answers, FAQ architecture, clean HTML, llms.txt, and a machine-readable knowledge base.

AI assistants read many more pages, search far more specific variants of a question, and lean on sources already trusted by search systems. Discoverability work optimizes for being citeable and recommendable, not just ranking.

Yes — a structured, source-of-truth content base (typically Markdown) that AI tools can use to answer questions about your brand consistently and correctly.

It ranges from a single scientific claim review to an evidence-based content sprint, an AI-discoverability audit, or a creator campaign. Tell me what you are working on and I will tell you whether it is a fit.

Both depend on scope. Share the project and I will send a range and a realistic timeline — rush options are sometimes available. Email collaborations@distilledscience.xyz.

Yes to all three. Health-tech and consumer-health brands, agencies, and early-stage startups are the most common fit.

Email collaborations@distilledscience.xyz with a sentence or two about your project, or see the media kit for audience, sponsorships, and rates.